---
title: Twilio Chatbot
sidebarTitle: Twilio Chatbot
---

In this tutorial, we'll use MindsDB's integration with Twilio and the custom Jobs feature to implement a chatbot that will reply to text messages. The replies will include a text response generated by OpenAI's GPT-4 model and an image response generated by the OpenAI's DallE 3 model.

<p align="center">
    <img src="/assets/twilio-chatbot-diagram.png" />
</p>

Read along to follow the tutorial.

## Step 1. Create OpenAI models with a bit of personality

In order to create an AI model, you’ll need an [OpenAI account](https://openai.com/) and an [API key](https://platform.openai.com/account/api-keys). You’ll also need a MindsDB installation - you can find an open-source version [here](https://github.com/mindsdb/mindsdb). 

Then go to your MindsDB SQL Editor and enter the following commands to create AI models:

**1. Model to generate a text response:**

    Before creating an OpenAI model, please create an engine, providing your OpenAI API key:

    ```sql
    CREATE ML_ENGINE openai_engine
    FROM openai
    USING
        openai_api_key = 'sk-xxx';
    ```

    Now you can create a model:

    ```sql
    CREATE MODEL twilio_bot_model
    PREDICT answer
    USING
    engine = 'openai_engine',
    max_tokens = 500,
    prompt_template = 'Pretend you are a mashup of Bill Murray and Taylor Swift. Provide a short description of an image using the style of Bill Murray and Taylor Swift that answers users questions: {{body}}';
    ```

    The `CREATE MODEL` command creates and deploys the model within MindsDB. Here we use the OpenAI GPT-3.5 Turbo model to generate text responses to users’ questions. The `prompt_template` message sets the personality of the bot - here, it is a mashup of Bill Murray and Taylor Swift.
    
    Please note that the `prompt_template` message contains the `{{body}}` variable, which will be replaced by the body of the received message upon joining the model with the table that stores messages.
    
    Let’s test it:
    
    ```sql
    SELECT body, answer
    FROM twilio_bot_model
    WHERE body = 'hey, can you draw a cat in the moon?';
    ```

    Here is a sample reply:

    <p align="center">
        <img src="/assets/twilio-text-model-response.png" />
    </p>

**2. Model to generate an image response:**

    We’ll use the OpenAI DallE 3 model to generate images as part of the responses.

    ```sql
    CREATE MODEL twilio_bot_image_model
    PREDICT img_url
    USING
    engine = 'openai_engine',
    mode = 'image',
    model_name = 'dall-e-3',
    prompt_template = 'Make a photorealistic image. Here is the description: {{answer}}, 4k, digital painting';
    ```

    The `CREATE MODEL` command creates and deploys the model within MindsDB. Here we use the OpenAI DallE 3 model to generate images based on the Billor Swift’s text response. The `prompt_template` message contains the `{{answer}}` variable. This variable is replaced by the prediction of the previous model upon chaining the two models.

    Let’s test it:

    ```sql
    SELECT textresponse.body, textresponse.answer, imageresponse.img_url
    FROM (SELECT body, answer
            FROM twilio_bot_model
            WHERE body = 'hey, can you draw a cat in the moon?') AS textresponse
    JOIN twilio_bot_image_model AS imageresponse;
    ```

    Here is a sample reply:

    <p align="center">
        <img src="/assets/twilio-image-model-response.png" />
    </p>

    The DallE 3 model provides a link to the generated image.

    <p align="center">
        <img src="/assets/twilio-image-model-image.png" />
    </p>

## Step 2. Set up your Twilio account and connect it to MinsdDB

You can set up a Twilio account [here](https://twilio.com/try-twilio), and then you get a virtual phone number in the console. This virtual number will be the one that sends a text to your personal number. 

Save the account string identifier (SID), auth token, and virtual phone number.

Use this command to connect the Twilio account to MindsDB:

```sql
CREATE DATABASE twilio
WITH
ENGINE = 'twilio',
PARAMETERS = {
   "account_sid":"todo",
   "auth_token":"todo"
};
```

Check out [this usage guide](https://github.com/mindsdb/mindsdb/tree/staging/mindsdb/integrations/handlers/twilio_handler#example-usage) to learn how to query and insert Twilio messages from MindsDB.

## Step 3. Automate the Twilio bot with MindsDB

We use the custom Jobs feature to schedule query execution.

```sql
CREATE JOB twilio_bot_images_job (

    INSERT INTO twilio.messages (to_number, from_number, body, media_url)
        SELECT outputtext.to_number AS to_number,
            outputtext.from_number AS from_number,
            outputtext.answer AS body,
            outputimage.img_url AS media_url
        FROM (
                SELECT input.from_number AS to_number,
                    input.to_number AS from_number,
                    output.answer AS answer
                FROM twilio.messages AS input
                JOIN twilio_bot_model AS output
                WHERE input.sent_at > LAST AND input.msg_status = 'received'
            ) AS outputtext
        JOIN twilio_bot_image_model AS outputimage
)
EVERY 2 minutes;
```

You can create a job using the `CREATE JOB` statement. Within parenthesis, provide all statements to be executed by the job. Finally, schedule a job - here it’ll run once every two minutes.

This job inserts replies to Twilio messages into the `messages` table. We provide the `SELECT` statement as an argument to the `INSERT` statement. Note that the inner `SELECT` statement uses one model to generate a text response (aliased as `outputtext`). Then, the output is joined with another model that generates an image (aliased as `outputimage`) based on the text response generated by the first model.

You can monitor this job with the following commands:

```sql
SELECT * FROM jobs
WHERE name='twilio_bot_images_job';
 
SELECT * FROM jobs_history
WHERE name='twilio_bot_images_job';
```

Here is a sample reply:

<p align="center">
    <img src="/assets/twilio-chatbot-response.png" />
</p>

<Tip>
Follow [this tutorial](https://mindsdb.com/blog/build-your-own-midjourney-in-sql) to create a Twitter chatbot.
</Tip>
